Proceedings of the 5th International Symposium on Knowledge Acquisition and Modeling

Object Tracking Using Meanshift Algorithm Combined with Kalman Filter on Robotic Fish

Authors
Li Xin, Xiang Wei
Corresponding Author
Li Xin
Available Online June 2015.
DOI
https://doi.org/10.2991/kam-15.2015.46How to use a DOI?
Keywords
meanshift algorithm; kalman filter; kernel function; target tracking.
Abstract

This paper investigates and proposes an improved Meanshift algorithm combined with Kalman Filter aiming at the shortcomings of the Meanshift algorithm theory as well as obvious limitations of a target tracking for the independent visual robotic fish being affected by the fluctuation of the water wave. First, this new algorithm makes use of Kalman filter to obtain the initial position of the Meanshift algorithm. Then, adjust the bandwidth of the kernel function adaptively in the Meanshift tracking algorithm and use the Meanshift algorithm to obtain the position of the tracking target. Finally, we conduct a real-time tracing experiment on the independent visual robotic fish tracking a moving ball. Experimental results show that: compared with the traditional Meanshift algorithm, the improved algorithm tracks the target more accurately and the trajectory of the tracking target is more continuous. Furthermore, it reduces the number of iterations, make the algorithm run faster and improve the real - time in tracking.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 5th International Symposium on Knowledge Acquisition and Modeling
Series
Advances in Intelligent Systems Research
Publication Date
June 2015
ISBN
978-94-62520-87-5
ISSN
1951-6851
DOI
https://doi.org/10.2991/kam-15.2015.46How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Li Xin
AU  - Xiang Wei
PY  - 2015/06
DA  - 2015/06
TI  - Object Tracking Using Meanshift Algorithm Combined with Kalman Filter on Robotic Fish
BT  - Proceedings of the 5th International Symposium on Knowledge Acquisition and Modeling
PB  - Atlantis Press
SP  - 168
EP  - 172
SN  - 1951-6851
UR  - https://doi.org/10.2991/kam-15.2015.46
DO  - https://doi.org/10.2991/kam-15.2015.46
ID  - Xin2015/06
ER  -